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Study Objectives: To characterize public practices and perspectives on the use of consumer sleep technology (CST) and evaluate perspectives on using CST as a screening tool for obstructive sleep apnea (OSA)., Methods: We designed a survey instrument incorporating content from validated instruments (STOP-BANG and the Epworth Sleepiness Scale) and hypothesis-generated questions. Survey development involved multidisciplinary collaboration among three board-certified sleep medicine experts, researchers, and consumers. The survey was disseminated across a national sample of adults living in the United States via an online platform., Results: Among 897 respondents, the mean (SD) age was 47.5 (16.9) years; 73.1% were female, 81.8% were White, and 505 respondents (56.3%) reported having tracked sleep using CS. Factors associated with decreased odds of CST use included household income <$30,000 (OR 0.47, 95% CI 0.28-0.79; p=0.004), Medicaid insurance (OR 0.43, 95% CI 0.26-0.69; p=0.001), Medicare insurance (OR 0.59, 95% CI 0.41-0.84; p=0.004), and lack of a primary care physician (OR 0.55, 95% CI 0.33-0.91; p=0.021). Most respondents (91.1%) agreed or strongly agreed that screening for OSA would be a useful feature of CST, but respondents reporting an education of high school diploma or less (OR 0.48, 95% CI 0.29-0.79; p=0.004) were less likely to agree with this statement., Conclusions: Attitudes toward and use of CST differed based on demographic and socioeconomic factors. Further study is needed to understand and address barriers to CST adoption and to characterize implications for equitable access to care for sleep disorders., (© 2024 American Academy of Sleep Medicine.)

Background: Inflammatory bowel disease (IBD) affects over 3 million Americans and has a relapsing and remitting course with up to 30% of patients experiencing exacerbations each year despite the availability of immune targeted therapies. An urgent need exists to develop adjunctive treatment approaches to better manage IBD symptoms and disease activity. Circadian disruption is associated with increased disease activity and may be an important modifiable treatment target for IBD. Morning light treatment, which advances and stabilizes circadian timing, may have the potential to improve IBD symptoms and disease activity, but no studies have explored these potential therapeutic benefits in IBD. Therefore, in this study, we aim to test the effectiveness of morning light treatment for patients with IBD., Methods: We will recruit sixty-eight individuals with biopsy-proven IBD and clinical symptoms and randomize them to 4-weeks of morning light treatment or 4-weeks of treatment as usual (TAU), with equivalent study contact. Patient-reported outcomes (IBD-related quality of life, mood, sleep), clinician-rated disease severity, and a biomarker of gastrointestinal inflammation (fecal calprotectin) will be assessed before and after treatment. Our primary objective will be to test the effect of morning light treatment versus TAU on IBD-related quality of life and our secondary objectives will be to test the effects on clinician-rated disease activity, depression, and sleep quality. We will also explore the effect of morning light treatment versus TAU on a biomarker of gastrointestinal inflammation (fecal calprotectin), and the potential moderating effects of steroid use, restless leg syndrome, and biological sex., Discussion: Morning light treatment may be an acceptable, feasible, and effective adjunctive treatment for individuals with active IBD suffering from impaired health-related quality of life., Trial Registration: The study protocol was registered on ClinicalTrials.gov as NCT06094608 on October 23, 2023, before recruitment began on February 1, 2024., (© 2024. The Author(s).)

Wearable sleep-tracking technology is of growing use in the sleep and circadian fields, including for applications across other disciplines, inclusive of a variety of disease states. Patients increasingly present sleep data derived from their wearable devices to their providers and the ever-increasing availability of commercial devices and new-generation research/clinical tools has led to the wide adoption of wearables in research, which has become even more relevant given the discontinuation of the Philips Respironics Actiwatch. Standards for evaluating the performance of wearable sleep-tracking devices have been introduced and the available evidence suggests that consumer-grade devices exceed the performance of traditional actigraphy in assessing sleep as defined by polysomnogram. However, clear limitations exist, for example, the misclassification of wakefulness during the sleep period, problems with sleep tracking outside of the main sleep bout or nighttime period, artifacts, and unclear translation of performance to individuals with certain characteristics or comorbidities. This is of particular relevance when person-specific factors (like skin color or obesity) negatively impact sensor performance with the potential downstream impact of augmenting already existing healthcare disparities. However, wearable sleep-tracking technology holds great promise for our field, given features distinct from traditional actigraphy such as measurement of autonomic parameters, estimation of circadian features, and the potential to integrate other self-reported, objective, and passively recorded health indicators. Scientists face numerous decision points and barriers when incorporating traditional actigraphy, consumer-grade multi-sensor devices, or contemporary research/clinical-grade sleep trackers into their research. Considerations include wearable device capabilities and performance, target population and goals of the study, wearable device outputs and availability of raw and aggregate data, and data extraction, processing, and analysis. Given the difficulties in the implementation and utilization of wearable sleep-tracking technology in real-world research and clinical settings, the following State of the Science review requested by the Sleep Research Society aims to address the following questions. What data can wearable sleep-tracking devices provide? How accurate are these data? What should be taken into account when incorporating wearable sleep-tracking devices into research? These outstanding questions and surrounding considerations motivated this work, outlining practical recommendations for using wearable technology in sleep and circadian research., (© The Author(s) 2023. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Objectives: Fibromyalgia is characterized by chronic widespread pain, mood, and sleep disturbance. Pharmacological treatments have modest efficacy and are associated with negative side effects, and alternative approaches are needed. Morning bright light treatment may assist in the management of fibromyalgia as it can reduce depressive symptoms, improve sleep, and advance circadian timing., Methods: Sixty people with fibromyalgia (58 women, mean age 41.8 ± 13.3 years) were enrolled in a study comparing 4 weeks of a 1-hour daily morning bright light treatment (active treatment) to a morning dim light treatment (comparison treatment). Both light treatments included behavioral procedures to stabilize sleep timing. The morning bright light treatment was expected to produce larger improvements in pain and function than the dim light treatment and larger improvements in potential mediators (mood, sleep, and circadian timing)., Results: Both the bright and dim light treatment groups achieved significant but similar levels of improvement in pain intensity, pain interference, physical function, depressive symptoms, and sleep disturbance. Overall, the sample on average displayed a clinically meaningful improvement in the Fibromyalgia Impact Questionnaire-Revised score (mean reduction of 11.2 points), comparable to that reported following physical exercise treatments. Minimal side effects were observed., Conclusions: Findings indicate that the effects of a morning bright light treatment did not exceed those of a comparison dim light treatment; yet the changes on average in both conditions revealed clinically meaningful improvements. Future research is warranted to identify what elements of this trial may have contributed to the observed effects., (© The Author(s) 2023. Published by Oxford University Press on behalf of the American Academy of Pain Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background: The past few years have seen a rapid emergence of artificial intelligence (AI)-enabled technology in the field of sleep medicine. AI refers to the capability of computer systems to perform tasks conventionally considered to require human intelligence, such as speech recognition, decision-making, and visual recognition of patterns and objects. The practice of sleep tracking and measuring physiological signals in sleep is widely practiced. Therefore, sleep monitoring in both the laboratory and ambulatory environments results in the accrual of massive amounts of data that uniquely positions the field of sleep medicine to gain from AI., Method: The purpose of this article is to provide a concise overview of relevant terminology, definitions, and use cases of AI in sleep medicine. This was supplemented by a thorough review of relevant published literature., Results: Artificial intelligence has several applications in sleep medicine including sleep and respiratory event scoring in the sleep laboratory, diagnosing and managing sleep disorders, and population health. While still in its nascent stage, there are several challenges which preclude AI's generalizability and wide-reaching clinical applications. Overcoming these challenges will help integrate AI seamlessly within sleep medicine and augment clinical practice., Conclusion: Artificial intelligence is a powerful tool in healthcare that may improve patient care, enhance diagnostic abilities, and augment the management of sleep disorders. However, there is a need to regulate and standardize existing machine learning algorithms prior to its inclusion in the sleep clinic., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Competing Interests: Dr. Burgess serves on the scientific advisory board for Natrol, LLC, and Moving Mindz, Pty Ltd, and is a consultant for F. Hoffmann-La Roche Ltd. Dr. Goldstein is the part inventor of a circadian rhythm mobile application licensed to Arcascope, LLC, on the medical advisory boards of Huxley Medical, Inc. and eviCore, and receives royalties from UpToDate. All other authors report no relevant financial or non-financial disclosures.

Mobile measures of human circadian rhythms (CR) are needed in the age of chronotherapy. Two wearable measures of CR have recently been validated: one that uses heart rate to extract circadian rhythms that originate in the sinoatrial node of the heart, and another that uses activity to predict the laboratory gold standard and central circadian pacemaker marker, dim light melatonin onset (DLMO). We first find that the heart rate markers of normal real-world individuals align with laboratory DLMO measurements when we account for heart rate phase error. Next, we expand upon previous work that has examined sleep patterns or chronotypes during the COVID-19 lockdown by studying the effects of social distancing on circadian rhythms. In particular, using data collected from the Social Rhythms app, a mobile application where individuals upload their wearable data and receive reports on their circadian rhythms, we compared the two circadian phase estimates before and after social distancing. Interestingly, we found that the lockdown had different effects on the two ambulatory measurements. Before the lockdown, the two measures aligned, as predicted by laboratory data. After the lockdown, when circadian timekeeping signals were blunted, these measures diverged in 70% of subjects (with circadian rhythms in heart rate, or CRHR, becoming delayed). Thus, while either approach can measure circadian rhythms, both are needed to understand internal desynchrony. We also argue that interventions may be needed in future lockdowns to better align separate circadian rhythms in the body., Competing Interests: OW has given talks at Unilever events and received honorariums/travel expenses. She is the CEO of Arcascope, a company that makes circadian rhythms software. DF is the CSO of Arcascope. They and the University of Michigan are part owners of Arcascope. Arcascope did not sponsor this research. CG receives royalties from UpToDate. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Huang, Mayer, Walch, Bowman, Sen, Goldstein, Tyler and Forger.)

Background: Although sleep disturbances are common among people with Multiple Sclerosis (PwMS), understanding of their impact has been stymied by limitations in approaches to sleep measurement within this population. The aim of this study was to comprehensively phenotype sleep patterns in PwMS through application of an emerging seven-domain framework that includes sleep duration, continuity, timing, quality, rhythmicity, regularity, and sleepiness., Methods: Sleep domains were estimated from wrist-worn accelerometry, Epworth Sleepiness Scale and Pittsburgh Sleep Quality Index responses. Extreme sleep values within each domain were constructed using previously published guidelines. A composite score of extreme values was calculated for each participant. Associations between sleep domains and severity of MS symptoms were explored (pain, fatigue, depressive symptoms, and cognitive dysfunction)., Results: Among n = 49 participants, median total sleep time was 456.3 min. Median time spent awake after sleep onset was 37 min. Sleepiness, abnormal sleep timing, and poor sleep quality affected 33%, 35%, and 45% of participants, respectively. Seventy-six percent had ≥2 sleep domains in extreme ranges. PwMS had longer sleep duration and decreased sleep regularity compared to a non-MS historical cohort of older men. Greater daytime sleepiness, poorer sleep quality, and higher composite sleep health score were associated with more depressive symptoms, and lower sleep rhythmicity was associated with higher fatigue. Associations were observed between measures of cognitive function and sleep fragmentation, duration, quality, rhythmicity, and composite score., Conclusion: Application of a seven-domain sleep health framework that captures the dynamic and multifaceted aspects of sleep is feasible in PwMS, and offers potential for an improved understanding of the scope and impact of sleep disturbances in PwMS., (Copyright © 2021. Published by Elsevier B.V.)

From smart work scheduling to optimal drug timing, there is enormous potential in translating circadian rhythms research results for precision medicine in the real world. However, the pursuit of such effort requires the ability to accurately estimate circadian phase outside of the laboratory. One approach is to predict circadian phase noninvasively using light and activity measurements and mathematical models of the human circadian clock. Most mathematical models take light as an input and predict the effect of light on the human circadian system. However, consumer-grade wearables that are already owned by millions of individuals record activity instead of light, which prompts an evaluation of the accuracy of predicting circadian phase using motion alone. Here, we evaluate the ability of four different models of the human circadian clock to estimate circadian phase from data acquired by wrist-worn wearable devices. Multiple datasets across populations with varying degrees of circadian disruption were used for generalizability. Though the models we test yield similar predictions, analysis of data from 27 shift workers with high levels of circadian disruption shows that activity, which is recorded in almost every wearable device, is better at predicting circadian phase than measured light levels from wrist-worn devices when processed by mathematical models. In those living under normal living conditions, circadian phase can typically be predicted to within 1 h, even with data from a widely available commercial device (the Apple Watch). These results show that circadian phase can be predicted using existing data passively collected by millions of individuals with comparable accuracy to much more invasive and expensive methods., (© Sleep Research Society 2021. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

Purpose: To examine associations between objectively measured sleep duration and sleep timing with odds of completion of an in vitro fertilization (IVF) cycle., Methods: This prospective cohort study enrolled 48 women undergoing IVF at a large tertiary medical center between 2015 and 2017. Sleep was assessed by wrist-worn actigraphy, 1-2 weeks prior to initiation of the IVF cycle. Reproductive and IVF cycle data and demographic and health information were obtained from medical charts. Sleep duration, midpoint, and bedtime were examined in relation to IVF cycle completion using logistic regression models, adjusted for age and anti-Müllerian hormone levels. A sub-analysis excluded women who worked non-day shifts to control for circadian misalignment., Results: The median age of all participants was 33 years, with 29% of women >35 years. Ten women had an IVF cycle cancelation prior to embryo transfer. These women had shorter sleep duration, more nocturnal awakenings, lower sleep efficiency, and later sleep timing relative to those who completed their cycle. Longer sleep duration was associated with lower odds of uncompleted IVF cycle (OR = 0.88; 95%CI 0.78, 1.00, per 20-min increment of increased sleep duration). Women with later sleep midpoint and later bedtime had higher odds of uncompleted cycle relative to those with earlier midpoint and earlier bedtime; OR = 1.24; 95%CI 1.09, 1.40 and OR = 1.33; 95%CI 1.17, 1.53 respectively, for 20-min increments. These results were independent of age, anti-Müllerian hormone levels, or sleep duration, and remained significant after exclusion of shift-working women., Conclusions: Shorter sleep duration and later sleep timing increase the odds of uncompleted cycles prior to embryo transfer., (© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Millions of wearable-device users record their heart rate (HR) and activity. We introduce a statistical method to extract and track six key physiological parameters from these data, including an underlying circadian rhythm in HR (CRHR), the direct effects of activity, and the effects of meals, posture, and stress through hormones like cortisol. We test our method on over 130,000 days of real-world data from medical interns on rotating shifts, showing that CRHR dynamics are distinct from those of sleep-wake or physical activity patterns and vary greatly among individuals. Our method also estimates a personalized phase-response curve of CRHR to activity for each individual, representing a passive and personalized determination of how human circadian timekeeping continually changes due to real-world stimuli. We implement our method in the "Social Rhythms" iPhone and Android app, which anonymously collects data from wearable-device users and provides analysis based on our method.

Circadian clocks control the timing of many physiological events in the 24-h day. When individuals undergo an abrupt external shift (e.g., change in work schedule or travel across multiple time zones), circadian clocks become misaligned with the new time and may take several days to adjust. Chronic circadian misalignment, e.g., as a result of shift work, has been shown to lead to several physical and mental health problems. Despite the serious health implications of circadian misalignment, relatively little is known about how genetic variation affects an individual's ability to entrain to abrupt external changes. Accordingly, we used the one-hour advance from the onset of daylight saving time (DST) as a natural experiment to comprehensively study how individual heterogeneity affects the shift of sleep/wake cycles in response to an abrupt external time change. We found that individuals genetically predisposed to a morning tendency adjusted to the advance in a few days, while genetically predisposed evening-inclined individuals had not shifted. Observing differential effects by genetic disposition after a one-hour advance underscores the importance of heterogeneity in adaptation to external schedule shifts. These genetic differences may affect how individuals adjust to jet lag or shift work as well., (© 2021. The Author(s).)

Study Objectives: Obstructive sleep apnea and other sleep disorders overlap with comorbidities associated with poor outcomes related to severe acute respiratory syndrome coronavirus 2 infection. However, the prevalence of obstructive sleep apnea among patients hospitalized for COVID-19 and relationship to outcomes is poorly characterized, and the relevance of other sleep disorders remains unknown. The objective of this study was to identify the prevalence of pre-existing sleep disorders and association with outcomes related to severe COVID-19 illness., Methods: Patients with severe acute respiratory syndrome coronavirus 2 infection admitted to the University of Michigan Hospital System were included. Electronic medical records were queried for sleep disorders diagnostic codes. Data were extracted from polysomnography and home sleep testing in a subgroup with previous diagnostic testing at our center. Logistic regression was used to examine the association of sleep disorders with mechanical ventilation requirement, treatment with vasopressors, and death and Cox proportional hazards regression for time to discharge., Results: Among n = 572 adult patients hospitalized for COVID-19, 113 (19.8%) patients had obstructive sleep apnea, 4 patients had central sleep apnea (0.7%), 5 had hypoventilation (0.9%), 63 had insomnia (11.0%), and 22 had restless legs syndrome or periodic limb movements disorder (3.9%). After adjusting for age, sex, body mass index, and race, no significant relationship was apparent between sleep disorders diagnoses or indices of sleep-disordered breathing severity and outcomes., Conclusions: This is the first study to determine the prevalence of obstructive sleep apnea and other sleep disorders in a well-characterized cohort of patients hospitalized for COVID-19. Once hospitalized, a significant contribution of sleep disorders to outcomes was not identified. Therefore, future evaluations should focus on earlier outcomes, such as infection or clinical manifestations after exposure to severe acute respiratory syndrome coronavirus 2., (© 2021 American Academy of Sleep Medicine.)

While 24-h total sleep time (TST) is established as a critical driver of major depression, the relationships between sleep timing and regularity and mental health remain poorly characterized because most studies have relied on either self-report assessments or traditional objective sleep measurements restricted to cross-sectional time frames and small cohorts. To address this gap, we assessed sleep with a wearable device, daily mood with a smartphone application and depression through the 9-item Patient Health Questionnaire (PHQ-9) over the demanding first year of physician training (internship). In 2115 interns, reduced TST (b = -0.11, p < 0.001), later bedtime (b = 0.068, p = 0.015), along with increased variability in TST (b = 0.4, p = 0.0012) and in wake time (b = 0.081, p = 0.005) were associated with more depressive symptoms. Overall, the aggregated impact of sleep variability parameters and of mean sleep parameters on PHQ-9 were similar in magnitude (both r 2  = 0.01). Within individuals, increased TST (b = 0.06, p < 0.001), later wake time (b = 0.09, p < 0.001), earlier bedtime (b = - 0.07, p < 0.001), as well as lower day-to-day shifts in TST (b = -0.011, p < 0.001) and in wake time (b = -0.004, p < 0.001) were associated with improved next-day mood. Variability in sleep parameters substantially impacted mood and depression, similar in magnitude to the mean levels of sleep parameters. Interventions that target sleep consistency, along with sleep duration, hold promise to improve mental health.

Study Objectives: By March 2020, COVID-19 forced much of the world to stay at home to reduce the spread of the disease. Whereas some health care workers transitioned to working from home, many continued to report to work in person as essential employees. We sought to explore changes in sleep, health, work, and mood in health care workers during the stay-at-home orders., Methods: We developed a cross-sectional online survey administered to health care workers. The survey assessed changes in sleep, work, screen time, media exposure, diet, exercise, substance use, and mood. The survey data were collected between March 28, 2020, and April 29, 2020., Results: A total of 834 of 936 individuals completed the entire survey. Respondents were from 41 US states. Mood after the stay-at-home orders worsened, and screen time and substance use increased. Total sleep time shortened in those continuing to work in person (P < .001), whereas it was unchanged in those working from home (P = .73). Those working from home went to bed later, woke up later, and worked fewer hours. Reduced total sleep time and increased screen time before bed were associated with worse mood and screen time. Longer sleep time was associated with better mood., Conclusions: Health care workers' mood worsened regardless of whether work was in person or remote, although total sleep time was shorter for those working in person. Those working from home may have shifted their sleep time to be more in line with their endogenous circadian phase. Peer or other support services may be indicated to address sleep, mood, and health behaviors among health care workers during these unprecedented times., (© 2021 American Academy of Sleep Medicine.)

Study Objectives: Opioids are known to contribute to central sleep apnea (CSA), but the influence of nonopioid central nervous system active medications (CNSAMs) on CSA remains unclear. In light of the hypothesized impact of nonopioid CNSAMs on respiration, we examined the relationships between the use of opioids only, nonopioid CNSAMs alone, and their combination with CSA., Methods: Among all adults who underwent polysomnography testing at the University of Michigan's sleep laboratory between 2013 and 2018 (n = 10,606), we identified 212 CSA cases and randomly selected 300 controls. Participants were classified into four groups based on their medication use: opioids alone, nonopioid CNSAMs only, their combination, and a reference group, including those who did not use any of these medications. We defined CSA as a binary outcome and as a continuous variable using central apnea index data. Logistic and linear regression were used to examine associations between medication use, CSA diagnosis, and central apnea index., Results: Study participants included 58% men, and mean age was 50 (± 14 standard deviation years. Nearly half of the study participants did not use opioids or nonopioid CNSAMs, 6% used opioids alone, 27% nonopioid CNSAMs alone, and 16% used a combination of these medications. In adjusted analyses, opioids-only users had a nearly twofold increase in CSA odds, whereas those who used a combination of opioids and nonopioid CNSAMs had fivefold higher odds of CSA relative to the reference group. In contrast, the use of nonopioid CNSAMs alone had protective associations with CSA., Conclusions: This report showed increased odds of CSA, particularly among patients with sleep complaints who were prescribed opioids in combination with nonopioid CNSAMs compared with those who did not use any of these medications., (© 2021 American Academy of Sleep Medicine.)

Consumer sleep technologies have rapidly evolved from wrist-worn activity trackers to multisensory products. These technologies reflect a widespread interest in sleep health, and their ubiquitous ownership allows for remote sleep monitoring. Therefore, these technologies may play a valuable role in telemedicine. However, clinical usefulness remains contested and is limited by a lack of transparency in data acquisition and analysis, and uncertain accuracy of consumer sleep technology-derived sleep metrics. Collaboration between manufacturers, sleep scientists, and clinical sleep medicine teams is required to produce useable, verified technologies that can enhance and personalize the care of patients with sleep disorders., (Copyright © 2020 Elsevier Inc. All rights reserved.)

None: Sleep medicine is well positioned to benefit from advances that use big data to create artificially intelligent computer programs. One obvious initial application in the sleep disorders center is the assisted (or enhanced) scoring of sleep and associated events during polysomnography (PSG). This position statement outlines the potential opportunities and limitations of integrating artificial intelligence (AI) into the practice of sleep medicine. Additionally, although the most apparent and immediate application of AI in our field is the assisted scoring of PSG, we propose potential clinical use cases that transcend the sleep laboratory and are expected to deepen our understanding of sleep disorders, improve patient-centered sleep care, augment day-to-day clinical operations, and increase our knowledge of the role of sleep in health at a population level., (© 2020 American Academy of Sleep Medicine.)

None: Polysomnography remains the cornerstone of objective testing in sleep medicine and results in massive amounts of electrophysiological data, which is well-suited for analysis with artificial intelligence (AI)-based tools. Combined with other sources of health data, AI is expected to provide new insights to inform the clinical care of sleep disorders and advance our understanding of the integral role sleep plays in human health. Additionally, AI has the potential to streamline day-to-day operations and therefore optimize direct patient care by the sleep disorders team. However, clinicians, scientists, and other stakeholders must develop best practices to integrate this rapidly evolving technology into our daily work while maintaining the highest degree of quality and transparency in health care and research. Ultimately, when harnessed appropriately in conjunction with human expertise, AI will improve the practice of sleep medicine and further sleep science for the health and well-being of our patients., (© 2020 American Academy of Sleep Medicine.)

Wearable, multisensor, consumer devices that estimate sleep are now commonplace, but the algorithms used by these devices to score sleep are not open source, and the raw sensor data is rarely accessible for external use. As a result, these devices are limited in their usefulness for clinical and research applications, despite holding much promise. We used a mobile application of our own creation to collect raw acceleration data and heart rate from the Apple Watch worn by participants undergoing polysomnography, as well as during the ambulatory period preceding in lab testing. Using this data, we compared the contributions of multiple features (motion, local standard deviation in heart rate, and "clock proxy") to performance across several classifiers. Best performance was achieved using neural nets, though the differences across classifiers were generally small. For sleep-wake classification, our method scored 90% of epochs correctly, with 59.6% of true wake epochs (specificity) and 93% of true sleep epochs (sensitivity) scored correctly. Accuracy for differentiating wake, NREM sleep, and REM sleep was approximately 72% when all features were used. We generalized our results by testing the models trained on Apple Watch data using data from the Multi-ethnic Study of Atherosclerosis (MESA), and found that we were able to predict sleep with performance comparable to testing on our own dataset. This study demonstrates, for the first time, the ability to analyze raw acceleration and heart rate data from a ubiquitous wearable device with accepted, disclosed mathematical methods to improve accuracy of sleep and sleep stage prediction., (© Sleep Research Society 2019. Published by Oxford University Press [on behalf of the Sleep Research Society].)

Purpose: Home sleep apnea tests (HSATs) are an alternative to attended polysomnograms (PSGs) when the pre-test probability for moderate to severe OSA is high. However, insurers often mandate use anytime OSA is suspected regardless of the pre-test probability. Our objective was to determine the ability of HSATs to rule in OSA when the pre-test probability of an apnea hypopnea index (AHI) in the moderate to severe range is low., Methods: Patients who underwent HSATs were characterized as low or high pre-test probability based on the presence of two symptoms of the STOP instrument plus either BMI > 35 or male gender. The odds of HSAT diagnostic for OSA dependent on pre-test probability was calculated. Stepwise selection determined predictors of non-diagnostic HSAT. As PSG is performed after HSATs that do not confirm OSA, false negative results were assessed., Results: Among 196 individuals, pre-test probability was low in 74 (38%) and high in 122 (62%). A lower percentage of individuals with a low versus high pre-test probability for moderate to severe OSA had HSAT results that confirmed OSA (61 versus 84%, p = 0.0002) resulting in an odds ratio (OR) of 0.29 for confirmatory HSAT in the low pre-test probability group (95% CI [0.146, 0.563]). Multivariate logistic regression demonstrated that age ≤ 50 (OR 3.10 [1.24-7.73]), female gender (OR 3.58[1.50-8.66]), non-enlarged neck circumference (OR 11.50 [2.50-52.93]), and the absence of loud snoring (OR 3.47 [1.30-9.25]) best predicted non-diagnostic HSAT. OSA was diagnosed by PSG in 54% of individuals with negative HSAT which was similar in both pre-test probability groups., Conclusion: HSATs should be reserved for individuals with high pre-test probability for moderate to severe disease as opposed to any individual with suspected OSA.

Abstract: Consumer sleep technologies (CSTs) are widespread applications and devices that purport to measure and even improve sleep. Sleep clinicians may frequently encounter CST in practice and, despite lack of validation against gold standard polysomnography, familiarity with these devices has become a patient expectation. This American Academy of Sleep Medicine position statement details the disadvantages and potential benefits of CSTs and provides guidance when approaching patient-generated health data from CSTs in a clinical setting. Given the lack of validation and United States Food and Drug Administration (FDA) clearance, CSTs cannot be utilized for the diagnosis and/or treatment of sleep disorders at this time. However, CSTs may be utilized to enhance the patient-clinician interaction when presented in the context of an appropriate clinical evaluation. The ubiquitous nature of CSTs may further sleep research and practice. However, future validation, access to raw data and algorithms, and FDA oversight are needed., (© 2018 American Academy of Sleep Medicine.)

Female shift workers are at increased risk for negative reproductive outcomes, and animal evidence suggests that manipulation of the light-dark cycle is detrimental to early gestation in female mice. Specifically, failure of implantation may be responsible for these findings. The objective of this study was to better delineate which reproductive processes are vulnerable to detrimental effects of maternal circadian disturbance. We exposed mice undergoing embryo transfer to repetitive phase advances of the photoperiod. Embryos were derived from donor sperm and eggs from mice living in normal light-dark conditions to isolate the effects of photoperiod disruption on uterine receptivity and early gestation. Twenty-eight mice receiving embryo transfer underwent an experimental light-dark condition (advance of lights on and lights off by 6 hours every 4 days). Twenty-eight mice remained in a normal light-dark condition. Animals lived in their assigned light-dark condition beginning 2 weeks prior to embryo transfer and ending the day of uterine necropsy (post-coitus day 14.5). Wilcoxon-Mann-Whitney test demonstrated no significant differences between control and experimental light-dark conditions in pups (Z=0.10, p=.92), resorptions (Z=0.20, p=.84), or implantations (Z=-0.34, p=.73). Pup and placental weights were similar between groups. In this investigation, uterine receptivity and maintenance of early gestation were preserved despite recurrent phase advances in photoperiod. This finding, in the context of the current literature, suggests that the negative effects of circadian disruption are mediated by reproductive processes upstream of implantation.

Objective: To demonstrate that commercial activity monitoring devices (CAMDs) are practical for monitoring resident sleep while on call. Studies that have directly monitored resident sleep are limited, likely owing to both cost and difficulty in study interpretation. The advent of wearable CAMDs that estimate sleep presents the opportunity to more readily evaluate resident sleep in physically active settings and "home call," a coverage arrangement familiar to urology programs., Methods: Twelve urology residents were outfitted with Fitbit Flex devices during "home call" for a total of 57 (out of 64, or 89%) call or post-call night pairs. Residents were surveyed with the Stanford Sleepiness Scale (SSS), a single-question alertness survey. Time in bed (TIB) was "time to bed" to "rise for day." Fitbit accelerometers register activity as follows: (1) not moving; (2) minimal movement or restless; or (3) above threshold for accelerometer to register steps. Total sleep time (TST) was the number of minutes in level 1 activity during TIB. Sleep efficiency (SE) was defined as TST divided by TIB., Results: While on call, 10 responding (of 12 available, 83%) residents on average reported TIB as 347 minutes, TST as 165 minutes, and had an SE of 47%. Interestingly, SSS responses did not correlate with sleep parameters. Post-call sleep demonstrated increases in TIB, SE, and TST (+23%, +15%, and +44%, respectively) while sleepiness was reduced by 22%., Conclusion: We demonstrate that urologic residents can consistently wear CAMDs while on home call. SSS did not correlate with Fitbit-estimated sleep duration. Further study with such devices may enhance sleep deprivation recognition to improve resident sleep., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Objective: Sleep disturbances are thought to be frequent in women undergoing IVF despite minimal research of this hypothesis. Our goal was to longitudinally assess sleep duration and disturbances in women undergoing IVF and assess impact of habitual sleep duration on oocytes retrieved, an important outcome in IVF., Methods: Actigraphy and questionnaire batteries containing sleep and psychometric instruments were performed prior to and throughout 24 IVF cycles., Results: TST <7 h was present in 46%, 57%, 69%, and 42% of baseline, stimulation, post-oocyte retrieval, and post-embryo transfer recordings. ESS >10 was noted in 24%, 33%, and 36% of cycles during baseline, stimulation, and post-embryo transfer. PSQI >5 was noted in 57%, 43%, and 29% of cycles during baseline, stimulation, and post-embryo transfer. TST (F = 2.95, p = 0.04) and ESS (F = 4.36, p = 0.02) were the only sleep metrics in which a significant main effect of time was found by mixed models analysis. The final linear regression model chosen by stepwise selection to best explain the variability in oocytes retrieved included anti-mullerian hormone, day three follicle stimulating hormone, and baseline TST and explained 40% of the variance in oocytes retrieved (adjusted R 2  = 0.40, p = 0.03). Although not statistically significant, a trend towards a linear association between baseline TST and oocytes retrieved was seen with an increase of oocytes retrieved by 1.5 for every hour increase in TST (p = 0.09)., Conclusions: This is the first study to describe, with subjective and objective measures, sleep disturbances present throughout the IVF cycle. Importantly, a trend towards a linear relationship between TST and oocytes retrieved was found in this pilot study. Sleep may be a modifiable target to improve outcomes in women undergoing IVF and further investigations are needed., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Abstract: Pruritus (itching) during the sleep period can present as a symptom of dermatological or systemic disease, or as a parasomnia. Sleep related scratching as a primary parasomnia, exclusively confined to sleep in the absence of coexisting dermatological disorders, has not been well described. This case series describes three such patients, and discusses potentially relevant pathophysiology that can underlie itching or pain. Such cases of sleep related scratching may merit nosologic classification apart from previously defined parasomnias., (© 2016 American Academy of Sleep Medicine.)

Restless legs syndrome (RLS) is a sensorimotor disorder that can cause significant discomfort, impaired quality of life, poor mood, and disturbed sleep. Because the disorder is chronic and associated with multiple comorbidities, RLS can be seen in an inpatient or perioperative setting. Certain characteristics of the hospitalized or surgical context can exacerbate or unmask RLS. Importantly, RLS and the associated discomfort and insomnia can prolong hospital stay and negatively impact outcomes. RLS medications should be continued during the hospital admission when possible. Avoidance of excessive phlebotomy and medications known to trigger RLS is helpful. Patients should increase activity when acceptable., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Study Objective: Esophageal manometry (Pes) is the gold standard to detect repetitive episodes of increased respiratory effort followed by arousal (RERAs). Because RERAs are not included in the apnea-hypopnea index (AHI), we often refer patients with symptoms of sleep disordered breathing (SDB) and AHI < 5 for a second polysomnogram (PSG) with Pes. Often, the second PSG will demonstrate AHI > 5, confirming a diagnosis of OSA. We speculate that in most cases of suspected SDB, Pes does not add further diagnostic data and that night-to-night variability in OSA severity results in a first false-negative study., Methods: We conducted a retrospective review of PSGs between 2008 and 2012 in adults with initial PSG negative for OSA followed by a second study (with or without Pes) within 6 mo., Results: Of 125 studies that met inclusion criteria, a second study was completed with Pes in 105 subjects. SDB was diagnosed in 73 subjects (68.5%) completing a second PSG with Pes: 49 (46.7%) received a diagnosis based on AHI, and 24 (22.8%) received a diagnosis based on Pes (p = 0.003). There were no statistically significant differences in the mean AHI change between the two PSGs in subjects who completed the second study with or without Pes., Conclusions: In patients with symptoms of SDB and initial PSG with AHI < 5, the majority met criteria for OSA on second PSG by AHI without additional information added by Pes. Because Pes is not widely available and is somewhat invasive, a repeat study without Pes may be sufficient to diagnose SDB., (© 2015 American Academy of Sleep Medicine.)

Abstract: The American Academy of Sleep Medicine (AASM) commissioned several Workgroups to develop quality measures for the care of patients with common sleep disorders, including adults with restless legs syndrome (RLS). Using the AASM process for quality measure development, the RLS Work-group developed three target outcomes for RLS management, including improving the accuracy of diagnosis, reducing symptom severity, and minimizing treatment complications. Seven processes were developed to support these outcomes. To achieve the outcome of improving accuracy of diagnosis, the use of accepted diagnostic criteria and assessment of iron stores are recommended. To realize the outcome of decreasing symptom severity, routine assessment of severity and provision of evidence-based treatment are recommended. To support the outcome of minimizing treatment complications, counseling about potential side effects and assessing for augmentation and impulse control disorders, when indicated, are recommended. Further research is needed to validate optimal practice processes to achieve best outcomes in adult patients with RLS., (© 2015 American Academy of Sleep Medicine.)

By the current definition, complex sleep apnea (CompSA) refers to the emergence of central sleep apnea (CSA) during the treatment of obstructive sleep apnea (OSA) with continuous positive airway pressure (CPAP). However, new-onset CSA has been described with use of other treatments for OSA, including tracheostomy, maxillofacial surgery, and mandibular advancement device. We present a patient with CSA beginning after endoscopic sinus and nasal surgery for nasal obstruction in the setting of mild OSA. This case highlights the importance of non-PAP mechanisms in the pathogenesis of CompSA.

Opinion Statement: With the growth of the 24-hour global marketplace, a substantial proportion of workers are engaged in nontraditional work schedules and frequent jet travel across multiple time zones. Thus, shift work disorder and jet lag are prevalent in our 24/7 society and have been associated with significant health and safety repercussions. In both disorders, treatment strategies are based on promoting good sleep hygiene, improving circadian alignment, and targeting specific symptoms.Treatment of shift work must be tailored to the type of shift. For a night worker, circadian alignment can be achieved with bright light exposure during the shift and avoidance of bright light (with dark or amber sunglasses) toward the latter portion of the work period and during the morning commute home. If insomnia and/or excessive sleepiness are prominent complaints despite behavioral approaches and adequate opportunity for sleep, melatonin may be administered prior to the day sleep period to improve sleep, and alertness during work can be augmented by caffeine and wake-promoting agents.For jet lag, circadian adaptation is suggested only for travel greater than 48 h, with travel east more challenging than travel west. Although advancing sleep and wake times and circadian timing for eastward travel with evening melatonin and morning bright light several days prior to departure can help avoid jet lag at the new destination, this approach may be impractical for many people, Therefore, strategies for treatment at the destination, such as avoidance of early morning light and exposure to late-morning and afternoon light alone or in conjunction with bedtime melatonin, can accelerate re-entrainment following eastward travel. For westward travel, a circadian delay can be achieved after arrival with afternoon and early-evening light with bedtime melatonin.Good sleep hygiene practices, together with the application of circadian principles, can improve sleep quality, alertness, performance, and safety in shift workers and jet travelers. However, definitive multicenter randomized controlled clinical trials are still needed, using traditional efficacy outcomes such as sleep and performance as well as novel biomarkers of health.